With the increasing demand for intelligent services, the sixth-generation (6G) wireless
networks will shift from a traditional architecture that focuses solely on a high transmission …

Reliable digital communication is a primary workhorse of the modern information age. The
disciplines of communication, coding, and information theories drive the innovation by …

We consider wireless transmission of images in the presence of channel output feedback.
From a Shannon theoretic perspective feedback does not improve the asymptotic end-to …

Deep unfolding is a method of growing popularity that fuses iterative optimization algorithms
with tools from neural networks to efficiently solve a range of tasks in machine learning …

With the development of deep learning (DL), natural language processing (NLP) makes it
possible for us to analyze and understand a large amount of language texts. Accordingly, we …

Designing codes that combat the noise in a communication medium has remained a
significant area of research in information theory as well as wireless communications …

Deep learning has been applied in physical-layer communications systems in recent years
and has demonstrated fascinating results that were comparable or even better than human …

Landmark codes underpin reliable physical layer communication, eg, Reed-Muller, BCH,
Convolution, Turbo, LDPC, and Polar codes: each is a linear code and represents a …

High quality data is essential in deep learning to train a robust model. While in other fields
data is sparse and costly to collect, in error decoding it is free to query and label thus …

This paper provides a comprehensive survey of recent advances in deep learning (DL)
techniques for channel coding problems. Inspired by the recent successes of DL in a variety …